Grant for Animation Research Awarded to RTD's Perkins-Buzo

Southern Illinois University



Grant for Animation Research Awarded to RTD's Perkins-Buzo

October 23, 2018

${image-alt} Assistant Professor Reid Perkins-Buzo


Assistant Professor Reid Perkins-Buzo of the Department of Radio, Television, and Digital Media (RTD) , won a  SIU Foundation Research Award Grant in the amount of $5,046.00 for his project titled Exploring and Developing New Ways of Doing Animation: Incorporating Artificial Intelligence and Machine Learning into the Animator’s Toolset.  Assistant Professor Perkins-Buzo teaches courses on animation, gaming, and technology and culture.  He is also a member of an interdisciplinary group working on digitizing the Buckminster Fuller artifacts held by Morris Library.  The awards were announced by Provost Meera Kommaraju at last Friday’s joint Foundation-Alumni Association Luncheon. 

H.D. Motyl, Chair of RTD, said that “Perkins-Buzo is an exceptionally forward-thinking media maker.  We’re excited about his project.” 

View Reid's profile. 

Here is Assistant Professor Perkins-Buzo’s abstract: 


The goal of the project is to explore and develop new ways of doing animation, incorporating artificial intelligence and machine learning into the animator’s toolset. A few efforts have been made at convolving one image with another using deep learning approaches, so that one image’s ”style” is introduced into another image’s content. An example would be Google’s Deep Dream algorithm and its subsequent implementations. However, much more can be done with convolutional neural networks. It is possible that the deep learning networks can propose unique solutions to animated backgrounds and character movement. Much as the addition of computer graphics tools ignited a renaissance of animation in the past twenty years, the development of artificial intelligence and deep learning tools may spark additional flourishing in the art form. This is an unprecedented exploration into the creation of computer animation, a groundbreaking project in the use of machine learning for story-driven computer graphics.